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Versioning built for
machine learning
Build with confidence
Stop gitignoring your data & models
Simplify your workflow by tracking all your ML assets in one place.
Branch, build, and remix for free
Git going quickly with existing projects, with built-in provenance.
Share apps and projects with 1 click
Showcase your work in the context where it was developed.
The Xet Ecosystem
Integrates with ML Libraries & Platforms
ML Flow
Hugging Face
PyTorch
Tensorflow
XGBoost
Visualize Data
VegaLite
CSV Summaries
Netron
Streamlit
DtreeViz (soon)
Workflow Orchestration
GitHub Actions
Xet Actions
Flyte (soon)
Data Access
S3
Iceberg (soon)
DuckDB
Deployment
Docker
Kubernetes
Capsules
Accelerate your development
Reliable reproducibility
Never worry about managing your project dependencies again. A single source of truth for how your ML assets were generated.
Always know what happened
Store snapshots performantly with minimal cost. Access historical data just as quickly as current snapshots.
Master model management
Efficiently track ensembles and fine-tuned models for deduplicated uploads, downloads, and storage.
Built-in discoverability
Automatic summaries and visualizations for instant context and understandability within your repository.
Visualize everything
CSV sketch summaries for tabular data. Easy Streamlit or Gradio app deployments for everything else.
Reveal revisions
Time travel on your visualizations. See how your data and models have evolved over time.
What others are saying
“As we performed our technical evaluation of XetHub, we found that it scaled well as our repo sizes got larger. It was easy to adopt and required almost no training for the engineers on the team. The usage-based pricing model makes it easy to align our costs with system utilization, unlike some other models based on team size.”
